Data Visualization 1890

Those readers studying the parallel histories of visual sensemaking, information design, information architecture, statistical graphics and or data visualization will know that long before Richard Saul Wurman, Edward Tufte, Karl Weik, Otto Neurath, Gerd Arntz, Isotype Institute, Jacques Bertin, Fritz Kahn, or Willard Brinton came along, there existed various forms of what we now call visual sensemaking or social sensemaking. For decades, it has been a set of professions in constantly changing evolution. It has been referred to by numerous names, fragmented in many directions, focused in various terrains with different skill-sets, tool-sets and purposes, but the work of unpacking and then explaining complexity has been around for more than 100 years. We love to find and study early visual sensemaking!

Shown here, from the Humantific Collection, are three examples of 19th century sensemaking in the societal context from Rand McNally World Atlas, published in 1890. Inside the atlas are a dozen beautiful diagrams that accompany hundreds of pages of maps and pictorial engravings.

Often, the individual creators’ names have been lost in history, but what they managed to create in 1890 with the tools of that era is rather amazing. Referred to in atlases of the day as “statistical diagrams” or “statistical graphics,” they were often visual depictions of data-driven facts focused on subjects such as Population, Race, Crop Yields, National Debt, Religions, School Enrollment, etc. Also appearing were more abstraction-based depictions (not based on data), such as visualizations of what the Solar System was perceived to be at that time in history.

In these 19th century data visulization examples, you can see the sensemaking device or technique of making comparisons. Depending on the subject, those comparisons might be from country to country, state to state, or year to year. More than one hundred years later, depictions of comparisons remain central to many sensemaking diagrams made today. Professional sensemakers know that comparisons provide context, and context aids in understanding.

As in the majority of data visualization being created today, most 19th century sensemaking work seen in atlases was focused on depicting past and present states. At Humantific, we call these pictures of Yesterday and Today.

Also fascinating is that more than one hundred years after these 1890s visual comparison models were published, the American organizational theorist Karl Weick was speculating, in a rather non-visual 1995ish way, on the dimensions of sensemaking in organizations, pointing out that in order to give meaning to the present, humans compare it to similar events from their past. Many such unsyncronized realizations can be found in the various literatures.

In the 19th century, thinking about what we might be tomorrow and then moving towards that picture was not part of the statistical diagrams business, as it is for some, but not all sensemakers today. The truth is, a significant part of the now-very-popular data visualization community is still generating pictures of yesterday and today, not fully understanding what is missing.

Of course, one can generate pictures of yesterday and today from data sets, but creating pictures of tomorrow requires additional dimensions of skill in the mix, including applied imagination, and cocreation.

Effectively cocreating such visual pictures in real time with humans from multiple disciplines in the room requires additional skill dimensions that were not in the mix in 1890, and in some circles are just being recognized today. Today at Humantific, we integrate past, present, and future visual realizations as part of cocreated change making. For more than 15 years, we have been operating on the understanding that data visualization, in itself, is not enough to drive and ensure changemaking. In the real world, 99.9% of the time, change making has to be socially constructed. In other words, it has to be cocreated. This is part of the everyday bridging work that we love to do.

Viewing historical examples of data visualization in person, having original material on hand helps to inspire and inform how we think about our own work today and to better understand how its different!